Role Description We are looking for a founding Head of Engineering to take our systems to the next level. This is a hands-on technical leadership role for someone who has built agentic AI systems in production. - Own software architecture and delivery: design, deploy, and operate systems at scale - Design and evolve our AI systems, including: - prompting and orchestration logic - context and retrieval systems (search, integrations, memory) - evaluation infrastructure (LLM-as-judge, regression testing) - expert feedback systems (building eval sets from their natural workflow) - Stay on the frontier of AI and legal AI - Hire, manage, and grow the engineering team (currently 3 FTEs) Qualifications - 10+ years of software engineering experience (3+ years in Python) - 5+ years in a technical leadership role with ownership over architecture, delivery, and production systems - Experience hiring and managing engineers - Built agentic AI systems in production, including: - goal-directed reasoning, planning, and tool use - multi-agent or sub-agent architectures - context management and memory systems - Built evaluation systems (e.g. LLM-as-judge, automated evals, regression testing) - Worked in an AI-native development environment (Claude Code, Cursor, Codex, etc.) - Product mindset - ideally from a successful startup environment - Enough frontend or workflow UI experience to collaborate across the product stack Benefits - Competitive salary + meaningful founding-level equity - Fully covered health, dental, and vision - Unlimited PTO - High-impact work at the core of a rapidly growing legal AI company Company Description Inhouse is the #1 AI lawyer for small to midsize businesses. We combine AI, our own law firm, and an expert feedback loop to deliver fast, compliant, high-quality legal work at a fraction of the cost and turnaround time of traditional firms. We grew revenue 1,500% last year and recently raised a $5M seed round from leading VCs and the former CEO & Cofounder of LegalZoom.

• Lead, mentor, and grow a team of DevOps and SRE engineers, fostering a culture of ownership, reliability, and continuous improvement • Own the strategy and execution of Axion's cloud infrastructure, CI/CD pipelines, observability stack, and incident response processes • Partner with Engineering and Product leadership to align infrastructure investments with product scalability and reliability goals • Drive a roadmap for infrastructure modernization, capacity planning, and cost efficiency across our cloud environments • Champion security and compliance best practices, working cross-functionally to maintain a strong security posture • Define and track SLOs, SLIs, and error budgets — and hold the team accountable to them • Be hands-on when it counts: debugging production issues, reviewing architecture decisions, and unblocking your team • Build and maintain the systems, tooling, and processes that let Axion's engineers ship fast with confidence

Title: Data Engineer - Enterprise Data Engineering and Analytics Location: Houston United States Job Description: The Data Engineer role is a pivotal position within the Enterprise Data Engineering & Analytics Department, supporting the design, build, and operationalization of integrated data pipelines and analytics solutions that enable MD Anderson's digital business initiatives. The Data Engineer works across the Context Engine framework to deliver end-to-end data engineering solutions while partnering closely with Enterprise Data Engineering & Analytics teams and other institutional stakeholders. The Data Engineer contributes to the mission of MD Anderson Cancer Center, a leading institution focused on cancer care, research, education, and prevention. In this role, the Data Engineer helps advance enterprise analytics capabilities by ensuring secure, governed, and reusable data assets that accelerate insights and improve time-to-solution across MD Anderson. Ideal Candidate Statement The ideal candidate for the Data Engineer role brings a bachelor's degree in computer science, preferred advanced education in analytics or computer science, hands-on experience building data pipelines in healthcare or research environments, and familiarity with modern cloud-based data platforms, hands-on use of Large Language Models (LLMs) in real-world projects, Python or Spark development, and analytics delivery. Epic data model exposure or certification and the ability to collaborate across technical and clinical teams are strongly preferred. Position Information Salary range based on a 40-hour work week: Minimum $106,500 - Midpoint $133,000 - Maximum $159,500 Work location: Houston, Texas or surrounding area preferred This Data Engineer role offers the opportunity to contribute directly to MD Anderson's mission by enabling high-quality, governed data that supports clinical, research, and operational analytics across the institution. The position provides exposure to enterprise-scale data engineering initiatives, collaboration with experienced engineering and data science professionals, and opportunities for continued learning and career growth while supporting a balanced and sustainable work environment. - Employer-paid medical coverage starting day one for employees working 30+ hours/week, plus optional group dental, vision, life, AD&D, and disability insurance. - Accruals for PTO and Extended Illness Bank, plus paid holidays, wellness, childcare, and other leave options. - Tuition Assistance Program after six months of service and access to extensive wellness, fitness, and employee resource groups. - Defined-benefit pension through the Teachers Retirement System, voluntary retirement plans, and employer-paid life and reduced salary protection programs. Responsibilities Data Engineering - End-to-End Solution Delivery - Participate in end-to-end solution delivery that increases information capabilities and realizes data value across the institution - Build and test end-to-end data pipelines across ingestion, curation, transformation, modeling, and consumption within the Context Engine framework - Integrate data governance processes across data provenance, security, data quality, ontology, and metadata management - Participate in planning, architecture, analysis, design, and build of data pipelines in partnership with IS, Data Offices, and Data Governance teams - Contribute to existing data pipelines spanning acquisition, integration, and consumption for defined use cases Data Curation, Modeling, and Governance - Build data curation pipelines including profiling, specification creation, cleansing, transforming, standardizing, mastering, harmonizing, validating, and aggregating data - Monitor and support data quality across the Context Engine - Incorporate repeatable solution designs and data models to support reuse and scalability - Promote effective data management practices and understanding of analytics across the enterprise Standards, Testing, and System Maintenance - Adhere to IS division standard operating procedures and all MD Anderson policies - Maintain build standards and governance oversight sign-off aligned with institutional data strategy - Participate in documentation preparation for enhancements or new technology - Perform quality control, testing, and peer review of analytics builds - Support system updates, releases, change control processes, and after-hours support as required Education, Training, and Collaboration - Train data scientists, analysts, end users, and data consumers on data pipelining and preparation techniques - Assist in establishing training plans and curricula for Context Engine tools - Provide institutional, department, and one-on-one training on EDEA deliverables - Support liaison relationships with customers and OneIS partners to deliver effective technical solutions Innovation and Continuous Improvement - Explore and promote modern tools, techniques, and architectures to automate data preparation and integration tasks - Improve productivity by reducing manual and error-prone processes - Model OneIS values through integrity, partnership, quality, and continuous improvement EDUCATION - Required: Bachelor's Degree - Preferred: Bachelor's in computer science, Master's degree Business Analytics, Computer Science, Information Technology, Data Science, or related. WORK EXPERIENCE - Required: 2 years Clinical, relevant healthcare information technology, or relevant business experience. or - Required: With preferred degree, no experience required. - May substitute required education with years of related experience on a one to one basis. - Preferred: 3-5 years creating data pipelines in a healthcare research environment, experience building and maintaining analytical reports and dashboards, problem solving skills and ability to translate business/clinical requirements into reliable data models, analytics & reporting- cloud data management solutions like Foundry, Fabric etc, data pipeline & ETL development -hands on experience designing, building and maintaining pipelines using python/spark, hands-on use of Large Language Models (LLMs) in real-world projects, such as integrating generative AI solutions into applications, workflows, or analytics platforms. Candidates should be familiar with prompt engineering, model evaluation, and responsible AI practices. Experience collaborating with cross-functional teams to deploy and scale LLM-powered features is highly desirable. - Preferred certifications: EPIC Cogito, Clarity, Caboodle, Clinical Data Model. Work location: Prefer a candidate in Houston Texas or surrounding area. LICENSES AND CERTIFICATIONS - Required: EPIC - EPIC Certification Must obtain at least one Epic Data Model certification (Clinical, Access, or Revenue) issued by Epic. within 180 Days OTHER REQUIREMENTS: Must pass pre-employment skills test as required and administered by Human Resources. The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition. This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment. Additional Information - Requisition ID: 179587 - Employment Status: Full-Time - Employee Status: Regular - Work Week: Days - Minimum Salary: US Dollar (USD) 106,500 - Midpoint Salary: US Dollar (USD) 133,000 - Maximum Salary : US Dollar (USD) 159,500 - FLSA: exempt and not eligible for overtime pay - Fund Type: Hard - Work Location: Remote (within Texas only) - Pivotal Position: Yes - Referral Bonus Available?: No - Relocation Assistance Available?: No #LI-Remote

The future is what you make it. Are you ready to make a difference, work on most impactful projects influencing our business and be at heart of revolution to create a resilient supply chain? In Supplier Quality Engineering (SQE) we’re finding innovative, collaborative ways to improve delivery and quality of our suppliers creating vital link between our supply chain, internal factories and our customers. Come be a part of team of future shapers that: - Proactively reviews suppliers, assess operational gaps to identify risks and takes systematic actions to develop a world class supplier. - Is globally responsible for all supplier development and quality improvement and sustainment. - Systematically drives Root Cause Corrective Action (RCCA) investigations to prevent defects. - Works directly with sourcing, business, engineering and our customers on strategies to improve product quality and delivery. - Identifies and leads the implementation of continuous improvement projects. - Are leaders creating a performance culture with our suppliers through coaching and technical engagement. The position requires breadth of technical experience across multiple programs and products, experience in managing globally diverse teams, effectively communicating with senior management, developing improvement strategies, handling multiple priorities, influencing, and solving complex problems.